Predictive direct torque control with reduced ripples for induction motor drive based on T‐S fuzzy speed controller

Finite‐state model predictive control (FS‐MPC) has been widely used for controlling power converters and electric drives. Predictive torque control strategy (PTC) evaluates flux and torque in a cost function to generate an optimal inverter switching state in a sampling period. However, the existing PTC method relies on a traditional proportional‐integral (PI) controller in the external loop for speed regulation. Consequently, the torque reference may not be generated properly, especially when a sudden variation of load or inertia takes place. This paper proposes an enhanced predictive torque control scheme. A Takagi‐Sugeno fuzzy logic controller replaces PI in the external loop for speed regulation. Besides, the proposed controller generates a proper torque reference since it plays an important role in cost function design. This improvement ensures accurate tracking and robust control against different uncertainties. The effectiveness of the presented algorithms is investigated by simulation and experimental validation using MATLAB/Simulink with dSpace 1104 real‐time interface.     

Asynchronous H∞ filtering for time delayed APF with MDADT based on T‐S fuzzy model

This paper investigates the H_∞ asynchronous filtering problem for active power filter (APF) systems with time delayed to monitor the states of these systems. APF system is represented by T‐S fuzzy model. The phenomenon of asynchronous often appears in the practical system. And in this paper, asynchronous means that the switching of the filters we designed has a lag to the switching of the system models. By using the MDADT and the Lyapunov‐Krasovskii function methods, the switching filtering error system is delay‐dependent stability and has the H_∞ performance. The filter parameter is solved by linear matrix inequalities (LMIs). A simulation example is given to show the efficiency of the proposed methods.     

An adaptive event‐triggering scheme for networked interconnected control system with stochastic uncertainty

This paper investigates the problem of adaptive event‐triggering scheme for networked interconnected systems to relieve the burden of the network bandwidth. The data releasing is triggered by an adaptive event‐triggering device. The triggering condition depends on the state information at both the latest releasing instant and the current sampling instant. The threshold of the triggering parameter is achieved online rather than a predetermined constant. Taking the network‐induced delays and the coupling delays of the subsystems into account, together with the hybrid adaptive event‐triggering scheme and the stochastic uncertainty, we propose an unified model of the networked interconnected system. Sufficient conditions for the mean square stability and stabilization of the interconnected systems are developed by using Lyapunov–Krasovskii functional approach. A co‐designed method is put forward to obtain the controller gains and the weight of the triggering condition simultaneously. Finally, an example is provided to demonstrate the design method. Copyright © 2016 John Wiley & Sons, Ltd.     

H∞ fuzzy static output feedback control of T‐S fuzzy systems based on fuzzy Lyapunov approach

This paper is concerned with the problem of H_∞ fuzzy static output feedback control for discrete‐time Takagi‐Sugeno (T‐S) fuzzy systems, and new design methods are presented. By defining a fuzzy Lyapunov function, a new sufficient condition guaranteeing the H_∞ performance of the T‐S fuzzy systems is derived, and the condition is expressed by a set of linear matrix inequalities. In comparison with the existing literature, the proposed approach may provide more relaxed condition while ensuring better H_∞ performance. The simulation results illustrate the effectiveness of the proposed approach. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

基于DFNN的动态矩阵网络控制系统的应用研究

针对网络控制系统中的随机时延,提出一种基于动态模糊神经网络的动态矩阵网络控制系统。利用动态模糊神经网络的特点,提高系统动态响应性能。在以太网的网络环境下,通过实验仿真结果表明,该方法响应快,提高了系统的跟踪精度,具有更理想的控制效果。     

Robust nonlinear variable selective control for networked systems

This paper is concerned with the networked control of a class of uncertain nonlinear systems. In this way, Takagi–Sugeno (T-S) fuzzy modelling is used to extend the previously proposed variable selective control (VSC) methodology to nonlinear systems. This extension is based upon the decomposition of the nonlinear system to a set of fuzzy-blended locally linearised subsystems and further application of the VSC methodology to each subsystem. To increase the applicability of the T-S approach for uncertain nonlinear networked control systems, this study considers the asynchronous premise variables in the plant and the controller, and then introduces a robust stability analysis and control synthesis. The resulting optimal switching-fuzzy controller provides a minimum guaranteed cost on an H₂ performance index. Simulation studies on three nonlinear benchmark problems demonstrate the effectiveness of the proposed method.     

Event-triggered fuzzy filtering in networked control system for a class of non-linear system with time delays

This paper focuses on the design of H _∞ filter and event-triggered scheme for a class of continuous non-linear networked control systems (NCSs) based on fuzzy system appeared with time delays. First, we consider the discrete event-triggered (ET) scheme to make efficient utilisation of bandwidth. Under this ET-scheme, sensor releases the data only when our sampled-data plant violates the specific event-triggered condition. Second, the T-S fuzzy system is used to model the non-linear NCSs. Another purpose of this paper is to design filters involving delays. Such filters have a more general form than the delay-free filters that have been mostly considered in the traditional studies. By using the time-delay system, co-design of event-triggered scheme and H _∞ filter for the delayed NCSs is presented in a unified frame work. To choose the latest data packet and discard the dis-ordered packet logic, zero-order hold is inserted between the fuzzy filter and event generator. Then, by using the novel fuzzy Lyapunov–Krasovskii function approach with free-weighting matrix technique, H _∞ filter design of event-triggered delay NCSs is proposed. Finally, to show the effective result of our co-design method, a tunnel-diode example is given.     

Robust H∞ static output‐feedback control for discrete‐time fuzzy systems with actuator saturation via fuzzy Lyapunov functions

In this paper, we present a new scheme for designing a H_∞ stabilizing controller for discrete‐time Takagi‐Sugeno fuzzy systems with actuator saturation and external disturbances. The weighting‐dependent Lyapunov functions approach is used to design a robust static output‐feedback controller. To address the input saturation problem, both constrained and saturated control input cases are considered. In both cases, stabilization conditions of the fuzzy system are formulated as a convex optimization problem in terms of linear matrix inequalities. Two simulation examples are included to illustrate the effectiveness of the proposed design methods. A comparison with the results given in recent literature on the subject is also presented.     

Robust control of T‐S fuzzy systems with time‐varying delay using new approach

This paper aims to design a controller to robustly stabilize uncertain nonlinear systems with time‐varying delay and norm bounded uncertainties via Takagi–Sugeno (T‐S) fuzzy model. The stabilization conditions are given in the form of linear matrix inequalities using a single Lyapunov–Krasovskii functional (LKF) combining the introduction of some relaxation matrices and only one tuning parameter. In comparison with the existing techniques in the literature, the proposed approach has two major advantages. The first is the reduction of computational complexity when the number of IF‐THEN rules, r, is big. The second concerns the conservatism reduction. Several examples are given to show the effectiveness and the merits of the design procedure. Copyright © 2009 John Wiley & Sons, Ltd.     

Robust Double‐integral T‐S Fuzzy Output Regulation for Nonlinear Systems

This paper proposes a robust double‐integral T‐S fuzzy output regulator design for affine nonlinear systems in the presence of parametric uncertainty and external disturbance. First, we adopt double integrators (an error integrator and an input integrator) to obtain an augmented T‐S fuzzy model representation which has a common input matrix of fuzzy rules. This property yields less stability conditions. Next, by introducing a set of virtual desired variables (VDVs), a double‐integral VDV‐based fuzzy regulator is proposed to cope with unknown bias and to achieve asymptotical output regulation. Afterward, the controller is simplified to avoid VDV calculation and enhance robustness to uncertainty and external disturbance. In contrast to traditional regulation design, the double‐integral non‐VDV fuzzy regulator design reduces the number of fuzzy controller rules and stability LMIs. Moreover, the error coordinate transformation is removed and the uncertainty is allowed in this paper. Finally, a DC/DC buck converter system is taken as the example to demonstrate the expected performance.     

A new method for control of nonlinear networked systems

Networked control of a class of nonlinear systems is considered. For this purpose, the previously proposed variable selective control (VSC) methodology is extended to the nonlinear systems. This extension is based upon the decomposition of the nonlinear system to a set fuzzy-blended locally linearized subsystems, and further application of the VSC methodology to each subsystem. Using the idea of parallel distributed compensation (PDC) method, the closed-loop stability of the overall networked system is guaranteed, using new linear matrix inequalities (LMIs). For the real-time implementation, real-time control signals are constructed for every entry of pre-specified vector of time delays, which is selected based on the presumed upper-bound of the network time delay. Similar to the traditional packet-base control methodology, such control signals are then packed as a control-side packet and transmitted back to a time delay compensator (TDC) located on the plant-side of the network. According to the most recent network time delay, the TDC selects just one entry of the control vector and applies it to the actuator through a zero order hold element. A sufficient condition for closed-loop asymptotic stability is determined. Simulation studies on nonlinear benchmark problems demonstrate the effectiveness of the proposed method.     

A nonlinear state‐feedback state‐feedforward tracking control strategy for a boiler‐turbine unit

A boiler‐turbine unit is a primary module for coal‐fired power plants, and an effective automatic control system is needed for the boiler‐turbine unit to track the load changes with the drum water level kept within an acceptable range. The aim of this paper is to develop a nonlinear tracking controller for the Bell‐Åström boiler‐turbine unit. A Takagi‐Sugeno fuzzy control system is introduced for the nonlinear modeling of the Bell‐Åström boiler‐turbine unit. Based on the Takagi‐Sugeno fuzzy models, a nonlinear tracking controller is developed, and the proposed control law is comprised of a state‐feedforward term and a state‐feedback term. The stability of the closed‐loop control system is analyzed on the basis of Lyapunov stability theory via the linear matrix inequality approach and Schur complement. Moreover, model uncertainties are also considered, and it is proved that with the proposed control law the tracking error converges to zero. To assess the performance of the proposed nonlinear state‐feedback state‐feedforward control strategy, a nonlinear model predictive control strategy and a linear strategy are presented as comparisons. The effectiveness and the advantages of the proposed nonlinear state‐feedback state‐feedforward control strategy are demonstrated by simulations.     

基于T-S模糊模型非线性网络控制系统改进H∞跟踪控制

研究一类非线性网络控制系统改进H∞跟踪控制问题, 该类网络控制系统中非线性被控对象和被跟踪对象分别采用Takagi-Sugeno(T-S)模糊模型和线性稳定参考模型描述. 首先通过综合考虑网络中的数据传输时滞和数据丢包影响, 采用输入时滞法和并行分布补偿技术, 建立基于零阶保持器刷新时刻的系统状态跟踪误差模型. 然后利用改进的自由权矩阵方法, 并结合Lyapunov直接法给出系统满足H∞跟踪性能的充分条件以及模糊控制器的设计方法. 最后仿真实例表明本文方法的有效性和相比已有方法的优越性.     

Relaxed fuzzy control synthesis of nonlinear networked systems under unreliable communication links

This paper proposes relaxed conditions for control synthesis of discrete-time Takagi–Sugeno fuzzy control systems under unreliable communication links. To widen the applicability of the fuzzy control approach under network environments, a novel fuzzy controller, which is homogenous polynomially parameter-dependent on both the current-time normalized fuzzy weighting functions and the multi-steps-past normalized fuzzy weighting functions, is provided to make much more use of the information of the underlying system. Moreover, a new kind of slack variable approach is also developed and thus the algebraic properties of these multi-instant normalized fuzzy weighting functions are collected into some augmented matrices. As a result, the conservatism of control synthesis of discrete-time Takagi–Sugeno fuzzy control systems under unreliable communication links can be significantly reduced. Two illustrative examples are presented to demonstrate the effectiveness of the theoretical development.     

网络化制造系统访问控制框架

建立SDACM对象模型的基础上,提出一个网络化制造系统的访问控制框架,研究了访问控制框架的工作流程以及框架与系统其他安全部件的关系。基于该框架开发的网络化制造原型系统在某企业应用中表明该框架能够满足网络化制造系统需求。     

Torque tracking control of electric load simulator with active motion disturbance and nonlinearity based on T‐S fuzzy model

This paper develops a high performance nonlinear control method for an electric load simulator (ELS). The tracking performance of the ELS is mainly affected by the actuator's active motion disturbance and friction nonlinearity. First, a nonlinear model of ELS is developed, and then the Takagi‐Sugeno fuzzy model is used to represent the friction nonlinearity ofthe ELS. A state observer is constructed to estimate the speed of the load system. For converting the tracking control into a stabilization problem, a new control design called virtual desired state synthesis is proposed to define the internal desired states. External disturbances are attenuated based on an H_∞ criterion and the stability of the entire closed‐loop model is investigated using the well‐known quadratic Lyapunov function. Meanwhile, the feedback gains and the observer gains are obtained separately by solving a set of linear matrix inequalities (LMIs). Both a simulation and experiment were performed to validate the effectiveness of the developed algorithm.     

Asymptotic and robust stability of T‐S fuzzy genetic regulatory networks with time‐varying delays

In this paper, we propose and investigate a new general model of fuzzy genetic regulatory networks described by the Takagi–Sugeno (T‐S) fuzzy model with time‐varying delays. By using a Lyapunov functional approach and linear matrix inequality (LMI) techniques, the stability criteria for the delayed fuzzy genetic regulatory networks are expressed as a set of LMIs, which can be solved numerically by LMI toolbox in Matlab. Two fuzzy genetic network example are given to verify the effectiveness and applicability of the proposed approach. Copyright © 2011 John Wiley & Sons, Ltd.     

球杆网络化控制系统的延时分析与控制方法研究

对球杆系统进行了机理建模,并针对球杆网络化控制系统网络负载小、节点少、带宽冗余等特点,从网络通信原理的角度分析了网络延时的不确定性,结合测试结果提出了具有时变性、分段保持性延时特征的网络环境的假设.在这个前提下,将网络分布时延转换为前向通道上的单一时延.在此基础上提出了球杆网络化控制系统的根据延时分段补偿控制的策略及在...     

Stability analysis for T–S fuzzy systems with interval time‐varying delays and nonlinear perturbations

This paper is concerned with the problem of the robust stability for T–S fuzzy systems with interval time‐varying delay and nonlinear perturbations. The key features of the approach include the introduction of uncorrelated augmented matrix items into the Lyapunov functional and the use of some appropriate integral inequalities. Unlike the existing methodologies, the proposed approach involves neither free weighting matrices nor any model transformation. It can, however, lead to much less conservative stability criteria than the existing ones for the systems under consideration. The cases of perturbations are assumed to both nonlinear time‐varying perturbations and time‐varying uncertainties in linear fractional form. Numerical examples show that the obtained results are less conservative than the existing ones in the literature. Copyright © 2009 John Wiley & Sons, Ltd.     

Application of two‐loop robust control to air‐conditioning systems

This paper presents the design and application of a two‐loop robust controller for temperature control in air‐conditioning systems. A Takagi‐Sugeno fuzzy model with uncertain local models is developed to describe the associated nonlinearities and uncertainties in the operation of the air handling units. Parallel distributed compensation is used to design the global control law. The local control law consists of two loops: an inner‐loop integral controller and an outer‐loop min‐max predictive controller with short prediction horizon. A discounting scheme is developed to weight the contribution of the two loops. Experimental results are presented which show that the proposed strategy can achieve acceptable control performance with a minimum of onsite tuning. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society